This paper investigates the role of mismatch between job seekers and job openings for the forecasting performance of a labor market matching function. In theory, higher mismatch lowers matching efficiency which increases the risk that the vacancies cannot be filled within the usual period of time. We investigate whether and to what extent forecasts of German job findings can be improved by a mismatch-enhanced labor market matching function. For this purpose, we construct so-called mismatch indicators that reflect regional, occupational and qualification-related mismatch on a monthly basis. In pseudo out-of-sample tests that account for the nested model environment, we find that forecasting models enhanced by the mismatch indicator significantly outperform their benchmark counterparts for all forecast horizons ranging between one month and a year. This is especially pronounced in the aftermath of the Great Recession where a low level of mismatch improved the possibility of unemployed to find a job again.